The present disclosure relates to decision support systems and more particularly to machines and methods that automatically determine parameters of the suggested actions to serve as input to a question-answering system that automatically generates questions, retrieves answers to such questions, and outputs impact confidence values for each answer indicating the degree of impact the answers have on the suggested actions.
Conventional decision support systems (such as those designed for a real-time command center) recommend optimized action plans to operators. Exemplary real-time command centers include traffic command centers, public transport command centers, emergency services command centers, and multiple-agency, or the so-called “smarter city” command centers. There are various ways in which such decision support systems (DSS) operate. In some cases, the DSS make use of rule-based, or so-called expert, systems which contain a series of “if-then” clauses to determine which actions are suggested at which times. In other cases, the DSS run a limited set of traffic simulations in real-time, based on the current conditions, to determine which decisions provide the best outcome, in simulation, and the DSS suggests those control actions to the operations staff. A DSS can include both offline and online phases, where the offline phase runs many simulations to determine likely outcomes, and the online phase uses simpler models allowing a faster response to a wider variety of actions and combinations.